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Author |
Affolder, A. et al; Garcia, C.; Lacasta, C.; Marco, R.; Marti-Garcia, S.; Miñano, M.; Soldevila, U. |
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Title |
Silicon detectors for the sLHC |
Type |
Journal Article |
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Year |
2011 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
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Volume  |
658 |
Issue |
1 |
Pages |
11-16 |
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Keywords |
Silicon particle detectors; Radiation damage; Irradiation; Charge collection efficiency |
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Abstract |
In current particle physics experiments, silicon strip detectors are widely used as part of the inner tracking layers. A foreseeable large-scale application for such detectors consists of the luminosity upgrade of the Large Hadron Collider (LHC), the super-LHC or sLHC, where silicon detectors with extreme radiation hardness are required. The mission statement of the CERN RD50 Collaboration is the development of radiation-hard semiconductor devices for very high luminosity colliders. As a consequence, the aim of the R&D programme presented in this article is to develop silicon particle detectors able to operate at sLHC conditions. Research has progressed in different areas, such as defect characterisation, defect engineering and full detector systems. Recent results from these areas will be presented. This includes in particular an improved understanding of the macroscopic changes of the effective doping concentration based on identification of the individual microscopic defects, results from irradiation with a mix of different particle types as expected for the sLHC, and the observation of charge multiplication effects in heavily irradiated detectors at very high bias voltages. |
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Address |
[Barber, T.; Breindl, M.; Driewer, A.; Koehler, M.; Kuehn, S.; Parzefall, U.; Preiss, J.; Walz, M.; Wiik, L.] Univ Freiburg, Inst Phys, D-79104 Freiburg, Germany, Email: Ulrich.Parzefall@physik.uni-freiburg.de |
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Publisher |
Elsevier Science Bv |
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English |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0168-9002 |
ISBN |
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Conference |
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Notes |
WOS:000297783300004 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
836 |
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Author |
ANTARES Collaboration (Ageron, M. et al); Aguilar, J.A.; Bigongiari, C.; Carmona, E.; Dornic, D.; Emanuele, U.; Gomez-Gonzalez, J.P.; Hernandez-Rey, J.J.; Mangano, S.; Real, D.; Roca, V.; Salesa, F.; Toscano, S.; Urbano, F.; Yepes, H.; Zornoza, J.D.; Zuñiga, J. |
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Title |
ANTARES: The first undersea neutrino telescope |
Type |
Journal Article |
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Year |
2011 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
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Volume |
656 |
Issue |
1 |
Pages |
11-38 |
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Keywords |
Neutrino; Astroparticle; Neutrino astronomy; Deep sea detector; Marine technology; DWDM; Photomultiplier tube; Submarine cable; Wet mateable connector |
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Abstract |
The ANTARES Neutrino Telescope was completed in May 2008 and is the first operational Neutrino Telescope in the Mediterranean Sea. The main purpose of the detector is to perform neutrino astronomy and the apparatus also offers facilities for marine and Earth sciences. This paper describes the design, the construction and the installation of the telescope in the deep sea, offshore from Toulon in France. An illustration of the detector performance is given. |
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Address |
[Barbarito, E; Cassano, B; Ceres, A; Circella, M; Fiorello, C; Mongelli, M; Montaruli, T; Ruppi, M] Ist Nazl Fis Nucl, Sez Bari, I-70126 Bari, Italy, Email: Marco.Circella@ba.infn.it |
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Publisher |
Elsevier Science Bv |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0168-9002 |
ISBN |
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Expedition |
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Conference |
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Notes |
WOS:000296129100003 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ elepoucu @ |
Serial |
785 |
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Author |
Panes, B.; Eckner, C.; Hendriks, L.; Caron, S.; Dijkstra, K.; Johannesson, G.; Ruiz de Austri, R.; Zaharijas, G. |
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Title |
Identification of point sources in gamma rays using U-shaped convolutional neural networks and a data challenge |
Type |
Journal Article |
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Year |
2021 |
Publication |
Astronomy & Astrophysics |
Abbreviated Journal |
Astron. Astrophys. |
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Volume |
656 |
Issue |
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Pages |
A62 - 18pp |
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Keywords |
catalogs; gamma rays: general; astroparticle physics; methods: numerical; methods: data analysis; techniques: image processing |
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Abstract |
Context. At GeV energies, the sky is dominated by the interstellar emission from the Galaxy. With limited statistics and spatial resolution, accurately separating point sources is therefore challenging. Aims. Here we present the first application of deep learning based algorithms to automatically detect and classify point sources from gamma-ray data. For concreteness we refer to this approach as AutoSourceID. Methods. To detect point sources, we utilized U-shaped convolutional networks for image segmentation and k-means for source clustering and localization. We also explored the Centroid-Net algorithm, which is designed to find and count objects. Using two algorithms allows for a cross check of the results, while a combination of their results can be used to improve performance. The training data are based on 9.5 years of exposure from The Fermi Large Area Telescope (Fermi-LAT) and we used source properties of active galactic nuclei (AGNs) and pulsars (PSRs) from the fourth Fermi-LAT source catalog in addition to several models of background interstellar emission. The results of the localization algorithm are fed into a classification neural network that is trained to separate the three general source classes (AGNs, PSRs, and FAKE sources). Results. We compared our localization algorithms qualitatively with traditional methods and find them to have similar detection thresholds. We also demonstrate the robustness of our source localization algorithms to modifications in the interstellar emission models, which presents a clear advantage over traditional methods. The classification network is able to discriminate between the three classes with typical accuracy of similar to 70%, as long as balanced data sets are used in classification training. We published online our training data sets and analysis scripts and invite the community to join the data challenge aimed to improve the localization and classification of gamma-ray point sources. |
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Address |
[Panes, Boris] Pontificia Univ Catolica Chile, Ave Vicuna Mackenna 4860, Macul, Region Metropol, Chile, Email: bapanes@gmail.com |
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Thesis |
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Publisher |
Edp Sciences S A |
Place of Publication |
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Language |
English |
Summary Language |
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Original Title |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0004-6361 |
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Expedition |
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Conference |
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Notes |
WOS:000725877600001 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ pastor @ |
Serial |
5053 |
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Author |
Amaldi, U.; Bonomi, R.; Braccini, S.; Crescenti, M.; Degiovanni, A.; Garlasche, M.; Garonna, A.; Magrin, G.; Mellace, C.; Pearce, P.; Pitta, G.; Puggioni, P.; Rosso, E.; Verdu-Andres, S.; Wegner, R.; Weiss, M.; Zennaro, R. |
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Title |
Accelerators for hadrontherapy: From Lawrence cyclotrons to linacs |
Type |
Journal Article |
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Year |
2010 |
Publication |
Nuclear Instruments & Methods in Physics Research A |
Abbreviated Journal |
Nucl. Instrum. Methods Phys. Res. A |
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Volume |
620 |
Issue |
2-3 |
Pages |
563-577 |
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Keywords |
Medical accelerators; Linac; Cyclotron; Synchrotron; Cyclinac; Radiation oncology; Hadrontherapy; Particle therapy; Proton therapy; Carbon ion therapy; Dose delivery |
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Abstract |
Hadrontherapy with protons and carbon ions is a fast developing methodology in radiation oncology. The accelerators used and planned for this purpose are reviewed starting from the cyclotrons used in the thirties. As discussed in the first part of this paper, normal and superconducting cyclotrons are still employed, together with synchrotrons, for proton therapy while for carbon ion therapy synchrotrons have been till now the only option. The latest developments concern a superconducting cyclotron for carbon ion therapy, fast-cycling high frequency linacs and 'single room' proton therapy facilities. These issues are discussed in the second part of the paper by underlining the present challenges, in particular the treatment of moving organs. |
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Address |
[Amaldi, U.; Bonomi, R.; Braccini, S.; Crescenti, M.; Degiovanni, A.; Garlasche, M.; Garonna, A.; Magrin, G.; Mellace, C.; Pearce, P.; Pitta, G.; Puggioni, P.; Rosso, E.; Andres, S. Verdu; Wegner, R.; Weiss, M.; Zennaro, R.] TERA Fdn, Novara, Italy, Email: Saverio.Braccini@cern.ch |
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Corporate Author |
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Thesis |
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Publisher |
Elsevier Science Bv |
Place of Publication |
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Editor |
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Language |
English |
Summary Language |
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Original Title |
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Series Editor |
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Series Title |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0168-9002 |
ISBN |
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Medium |
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Area |
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Expedition |
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Conference |
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Notes |
ISI:000280601700058 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
yes |
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Call Number |
IFIC @ elepoucu @ |
Serial |
401 |
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Author |
Gammaldi, V.; Zaldivar, B.; Sanchez-Conde, M.A.; Coronado-Blazquez, J. |
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Title |
A search for dark matter among Fermi-LAT unidentified sources with systematic features in machine learning |
Type |
Journal Article |
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Year |
2023 |
Publication |
Monthly Notices of the Royal Astronomical Society |
Abbreviated Journal |
Mon. Not. Roy. Astron. Soc. |
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Volume |
520 |
Issue |
1 |
Pages |
1348-1361 |
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Keywords |
astroparticle physics – methods; data analysis – methods; observational – methods; statistical – dark matter – gamma-rays; general |
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Abstract |
Around one-third of the point-like sources in the Fermi-LAT catalogues remain as unidentified sources (unIDs) today. Indeed, these unIDs lack a clear, univocal association with a known astrophysical source. If dark matter (DM) is composed of weakly interacting massive particles (WIMPs), there is the exciting possibility that some of these unIDs may actually be DM sources, emitting gamma-rays from WIMPs annihilation. We propose a new approach to solve the standard, machine learning (ML) binary classification problem of disentangling prospective DM sources (simulated data) from astrophysical sources (observed data) among the unIDs of the 4FGL Fermi-LAT catalogue. We artificially build two systematic features for the DM data which are originally inherent to observed data: the detection significance and the uncertainty on the spectral curvature. We do it by sampling from the observed population of unIDs, assuming that the DM distributions would, if any, follow the latter. We consider different ML models: Logistic Regression, Neural Network (NN), Naive Bayes, and Gaussian Process, out of which the best, in terms of classification accuracy, is the NN, achieving around 93 . 3 per cent +/- 0 . 7 per cent performance. Other ML evaluation parameters, such as the True Ne gativ e and True Positive rates, are discussed in our work. Applying the NN to the unIDs sample, we find that the de generac y between some astrophysical and DM sources can be partially solved within this methodology. None the less, we conclude that there are no DM source candidates among the pool of 4FGL Fermi-LAT unIDs. |
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Address |
[Gammaldi, V; Sanchez-Conde, M. A.; Coronado-Blazquez, J.] Univ Autonoma Madrid, Departamentode Fis Teor, E-28049 Madrid, Spain, Email: viviana.gammaldi@uam.es; |
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Thesis |
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Publisher |
Oxford Univ Press |
Place of Publication |
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Language |
English |
Summary Language |
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Abbreviated Series Title |
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Series Volume |
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Series Issue |
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Edition |
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ISSN |
0035-8711 |
ISBN |
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Conference |
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Notes |
WOS:000937053400014 |
Approved |
no |
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Is ISI |
yes |
International Collaboration |
no |
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Call Number |
IFIC @ pastor @ |
Serial |
5489 |
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